Minimum Energy Pathways via Quantum Monte Carlo

TL;DR

This paper demonstrates that quantum Monte Carlo (QMC) methods can accurately determine minimum energy pathways and transition states in chemical reactions, outperforming density functional theory (DFT) especially in challenging cases.

Contribution

The study introduces a QMC approach for reaction pathways that is transferable to larger systems and more accurate than DFT and traditional quantum chemistry methods.

Findings

QMC yields more accurate geometries and barriers than DFT.

QMC can locate transition states where DFT fails.

QMC is feasible for larger, complex systems.

Abstract

We perform quantum Monte Carlo (QMC) calculations to determine minimum energy pathways of simple chemical reactions, and compare the computed geometries and reaction barriers with those obtained with density functional theory (DFT) and quantum chemistry methods. We find that QMC performs in general significantly better than DFT, being also able to treat cases in which DFT is inaccurate or even unable to locate the transition state. Since the wave function form employed here is particularly simple and can be transferred to larger systems, we suggest that a QMC approach is both viable and useful for reactions difficult to address by DFT and system sizes too large for high level quantum chemistry methods.